PyCharm: PyCharm 2019.1 EAP 2

Our Early Access Program (EAP) continues, and we have some great features in this second version:

New in PyCharm

Syntax Highlighting in Vagrantfiles

Vagrant Highlighting

If you’re developing an application that will be deployed in a virtual machine, Vagrant is a great tool to automate the creation and deletion of your VM while you’re developing. Even though PyCharm has long had support for running Python code in a Vagrant box using the Vagrant interpreter, we haven’t had any support for Vagrantfiles until now.

Haven’t tried Vagrant before? Read our blog post on developing with Vagrant and Ansible, to prepare for deploying an application on Amazon EC2.

Sudo Support for SSH Interpreters

SSH Root

Writing some administration automation scripts? Or experimenting with GPIO on your Raspberry Pi? You’ll need root privileges to execute your scripts. PyCharm now let’s you run scripts with elevated privileges over SSH, letting you debug these scripts as easily as a any other script.

Further Improvements


Download this EAP from our website. Alternatively, you can use the JetBrains Toolbox App to stay up to date throughout the entire EAP.

If you’re on Ubuntu 16.04 or later, you can use snap to get PyCharm EAP, and stay up to date. You can find the installation instructions on our website.

PyCharm 2019.1 is in development during the EAP phase, therefore not all new features are already available. More features will be added in the coming weeks. As PyCharm 2019.1 is pre-release software, it is not as stable as the release versions. Furthermore, we may decide to change and/or drop certain features as the EAP progresses.

All EAP versions will ship with a built-in EAP license, which means that these versions are free to use for 30 days after the day that they are built. As EAPs are released weekly, you’ll be able to use PyCharm Professional Edition EAP for free for the duration of the EAP program, as long as you upgrade at least once every 30 days.

Planet Python

Analytics Explained: The Foundation

process of analytics

Call me crazy, but I think this whole data thing has legs. At this point, it’s a cliché to say that data is the new oil or that data maturity is vital to the business. Everybody wants to be a data-driven company, but often the mantras we espouse don’t quite make it into the day-to-day work of our employees.

From mom-and-pop stores to Fortune 100 companies, many of the same fundamental issues crop up: tunnel vision from focusing only on current needs; lack of proper infrastructure to support current needs (let alone future needs); and a glut of manual processes that are error prone and time consuming.

What Is Analytics Really?

If this sounds familiar, maybe it’s time to take a step back and do an honest assessment of your capabilities and structure. This should be a comprehensive look at your processes, training, people, tools and infrastructure to help you understand exactly where you are and what gaps you are currently experiencing. Usually, in consulting, this is where we pull out a maturity model and give you a rating on some arbitrary scale. However, I think we both know that the analytics world is more complicated than a simple A to B linear progression.

So, if it’s not a simple progression from descriptive analytics to prescriptive analytics, then what is analytics? Analytics is using data to generate insight and drive action to produce value. It’s a self-reinforcing cycle that builds upon itself. That cycle is supported by an ecosystem that needs to be healthy for it to thrive. We’ll tackle each of these aspects in this series of posts, but for now, let’s dig into the nuts and bolts of analytics.

Analytics Is About Value

When we bring on new consultants, I always give a talk to help them understand artificial intelligence, machine learning and data science. Over time, I found I needed to start at the very beginning to help others better understand the landscape because no matter what the industry hype tells you, you can’t start your analytics journey with neural networks and expect to succeed.

Analytics starts with using data to describe our world. From there, it moves to finding patterns in order to more fully understand what’s happening below the surface. It then ultimately leads us to apply our knowledge to produce models. Within each type, we are creating more and more business value.

process of analytics

The next blog post in this series will focus on the first kind of analytics—descriptive analytics—so be on the lookout for a deeper dive into the analytics essentials.

The post Analytics Explained: The Foundation appeared first on InterWorks.


codingdirectional: Add one to the last element of a list

Hello and welcome to another one day one answer series. In this article, we will create a python method which will do the following actions.

  1. Takes in a list of numbers.
  2. If the number is less than 0 or it is a double digits number then returns None.
  3. If it is an empty list then returns None.
  4. Else joins the numbers in the list together to create a larger number, for example, if a list consists of [1, 2, 3] then the larger number will become 123. Next, add one to that new number, so 123 becomes 124.
  5. Finally turns that new number back to a list, so 124 becomes [1, 2, 4] and returns that new list.

Below is the solution for this question.

 def up_array(arr):      str_ = ''        if(len(arr) == 0):         return None              for num in arr:         if(num < 0 or num > 9):             return None         else:             str_ += str(num)          total = str(int(str_) + 1)     arr = []      for number in total:         arr.append(int(number))      return arr 

That is it, hope you like this article.


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Planet Python

Advance with Assist: How to Exceed Tableau’s Column or Row Limit

forklift method in Tableau

Question: I need to add more than 16 columns to my sheet. How is this possible?

Let me start by saying that this is not recommended by InterWorks. If we are using this many rows or columns to create a crosstab view, there is likely a better software available for the task or a better way to visualize the data in Tableau itself. That being said, we see this when clients are tooling Tableau to mimic an Excel spreadsheet or craft a simple text view to be distributed on a printout.

What is Currently Possible in Tableau

Tableau typically only allows six dimensions across our Rows in a view like the one below:

default Rows view in Tableau

I can change this to allow up to 16 dimensions from Analysis > Table Layout > Advanced:

advanced table layout in Tableau

Two Ways to Exceed Tableau’s Column Limit

The first comes from a 2015 Tableau Conference session called “Use Tableau Like a Sith.”

Step 1: After going to Analysis >Table Layout > Advanced and changing the number in Rows and/or Columns to 16, save your workbook as a .twb.

Step 2: Open this file in Notepad.

Step 3: Search for the text: attr=’row-levels’.

  • <format attr=’row-levels’ value=’16’ />
  • <format attr=’row-horiz-levels’ value=’16’ />

Change the value of 16 to however many rows or columns you need.

Step 4: Save the Notepad file.

Step 5: Re-open your workbook in Tableau.

The second way is what some Tableau users call the Forklift method. Essentially, we will be using axes to trick Tableau into giving us more locations to place data fields.

Step 1: Create a parameter with a float value of 1. These are the default settings. Keep these:

default parameter settings in Tableau

Step 2: Place this field on Columns for however many extra columns you need to add.

Step 3: Use the Marks cards to place separate fields onto Text separate Marks. Switch the Mark Type to Text:

forklift method in TableauStep 4: Right-click the axis at the bottom to Edit Axis. Change the ranges to be Fixed for each axis. The field will always be displayed at the value of 1.

  • For left-justified, try a range of 0 to 3
  • For centered, 0 to 2
  • For right-justified, 0 to 1.6

When done, hide the axes by right-clicking and unchecking Show Header.

Step 5: Finalize the formatting by removing grid lines, zero lines and any borders you don’t want.

  • Right-click in the sheet and select Format, or use the Format drop-down menu from the top of the window.

Managing Multiple Axes Instances

It is possible to manage many instances of these axes, depending on the size of your monitor. I could fit 55 different Marks cards on my monitor; with the 16-field limit, that got me to a total of 71 columns. Each axis would have to be individually given a range, and each field would have to be placed on its respective Marks card, so managing this method is labor intensive.

To reiterate, it is not recommended to use Tableau in this way, but this is a stretch solution for those times when it is unavoidable.

The post Advance with Assist: How to Exceed Tableau’s Column or Row Limit appeared first on InterWorks.